Constraining sub-seismic deep-water stratal elements with electrofacies analysis; A case study from the Upper Cretaceous of the Måløy Slope, offshore Norway. (January 2015)

• Record Type: Journal Article
• Authors: Prélat, Amandine; Hodgson, David M.; Hall, Mark; Jackson, Christopher A.-L.; Baunack, Carol; Tveiten, Bjarne
• Is Part Of: Marine and petroleum geology. Volume 59(2015:Jan.)
• Page Start: 268
• Page End: 285
• Publication Date: 2015-01
• Subjects: Electrofacies -- Well data -- Måløy Slope -- Deep-water deposit -- Glauconite -- Artificial neural network; Submarine geology -- Periodicals; Petroleum -- Geology -- Periodicals; Géologie sous-marine -- Périodiques; Pétrole -- Géologie -- Périodiques; Petroleum -- Geology; Submarine geology; Periodicals; Electronic journals; 551.468
• DOI: 10.1016/j.marpetgeo.2014.07.018
• Languages: English
• ISSNs: 0264-8172

Abstract

Abstract: Electrofacies represent rock facies identified from wireline-log measurements, and allow extrapolation of petrophysical characteristics away from stratigraphic intervals that are calibrated to core. This approach has been employed to reduce uncertainty in the identification of the sub-seismic depositional elements in the late Cenomanian–Coniacian succession of the northern Måløy Slope, offshore Norway. Core logging permits identification of eleven distinct sedimentary facies that are grouped into four facies associations: FA A-turbidite sandstones, FA B-heterolithic siltstones and sandstones, FA C-debrites and FA D-slide and slump deposits. Each facies association is defined by a distinct combination of petrophysical characteristics, including porosity, density, gamma-ray, sonic and resistivity. Using neural network analysis, electrofacies are calibrated with sedimentary facies, thereby allowing us to map their thickness and stacking patterns within the studied deep-water succession. We demonstrate that this approach is particularly useful where the presence of glauconite makes the distinction between sandstone- from shale-rich units difficult using gamma-ray logs alone. Our results indicate that the succession of interest is dominated by debris flows and slide and slump deposits, which are commonly poorly imaged on seismic reflection datasets in the northern North Sea. The methodology presented here can aid the correlation of deep-water stratal elements at production and exploration scales in stratigraphic successions that have undergone similar burial histories.Furthermore, this method may help in the identification of mass flow deposits that are present in Upper Cretaceous deep-water systems of the North Sea. Highlights: Core and wireline logs from four wells are used to identify facies associations. Using neural network, electrofacies are calibrated with core facies. The Upper Cretaceous succession of the Måløy Slope is studied in details. Results show that the succession is dominated by mass transport deposits.